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Nonlinear Control Seminar
Quantum Mechanics with Control Theory

Gregory J. Toussaint


Date: 11 August 1999

Given a system described by a differential equation:

\begin{displaymath}\dot{x} = f(x,u,t), \hspace{2em} x(0) = x_0
\end{displaymath}

and a cost function to be optimized

\begin{displaymath}J_{[t,t_f]} \, (u) = q(t_f, x(t_f)) + \int_t^{t_f} g(x(s), u(s), s)\,
ds
\end{displaymath}

define the optimal cost as

\begin{displaymath}V(t,x) := \min_{u_{[t,t_f]}} J_{[t,t_f]} \, (u).
\end{displaymath}

Dynamic programming leads to an HJB equation:

\begin{eqnarray*}- V_t(t,x) & = & \min_{u \in \mathcal{U}} \left\{ V_x(t,x) \cdot
f(x,u,t) + g(x,u,t) \right\} \\
V(t_f, x) & = & q(t_f, x).
\end{eqnarray*}


We could also use a Lagrangian to derive the minimum principle. Let H be the Hamiltonian and $\ensuremath{p^{T}} $ be the co-state vector.

\begin{eqnarray*}H & = & g(x,u,t) + \ensuremath{p^{T}}\, f(x,u,t) \\
\dot{p} & ...
...} & = & f(x,u,t) \;\;=\;\; H_{p} \, , \hspace{2em} x(t_0) = x_0.
\end{eqnarray*}



 
Table: Operators used in quantum mechanics.
Quantity Symbol   Operator Form
Momentum x px   $\frac{\hbar}{i} \ensuremath{\frac{\partial
}{\partial x}} $
Kinetic Energy $\frac{p^2}{2m}$   $- \frac{\hbar^2}{2m} \left[
\ensuremath{\frac{\partial^2
}{\partial x^2}} + \en...
...rtial^2
}{\partial y^2}} + \ensuremath{\frac{\partial^2
}{\partial z^2}}\right]$
Kinetic Energy T   $-\frac{\hbar}{i} \ensuremath{\frac{\partial
}{\partial t}} $
Potential Energy V   V(qi)


  
Figure: Dynamic programming with complex trajectories.
\begin{figure}
\centering
\begin{tabular}{c}
\setlength{\unitlength}{0.0006666...
...default}{\updefault}$\xi + n z$ }}}}}
\end{picture}}
\end{tabular} \end{figure}

Consider:








 
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Gregory J. Toussaint
1999-08-11